Charlet Jean, Cui Licong
Sorbonne Université, INSERM, Univ Sorbonne Paris Nord, LIMICS, Paris, France.
AP-HP, DRCI, Paris, France.
Yearb Med Inform. 2024 Aug;33(1):223-226. doi: 10.1055/s-0044-1800748. Epub 2025 Apr 8.
We aim to identify, select, and summarize the best papers published in 2023 for the Knowledge Representation and Management (KRM) section of the International Medical Informatics Association (IMIA) Yearbook.
We performed PubMed queries and adhered to the IMIA Yearbook guidelines for conducting biomedical informatics literature review to select the best papers in KRM published in 2023.
Our search yielded a total of 1,666 publications from PubMed. From these, we identified 15 papers as potential candidates for the best papers, and three of them were finally selected as the best papers in the KRM section. The candidate best papers covered three main topics: knowledge graph, knowledge interoperability, and ontology. Notably, two of the three selected best papers explored the potential of knowledge graph embeddings for predicting intensive care unit readmissions and measuring disease distances, respectively.
The selection process for the best papers in the KRM section for 2023 showcased a wide spectrum of topics, with knowledge graph embeddings emerging as a promising area for supporting machine learning applications in biomedicine.
我们旨在识别、挑选并总结2023年发表的有关国际医学信息学协会(IMIA)年鉴知识表示与管理(KRM)部分的最佳论文。
我们进行了PubMed检索,并遵循IMIA年鉴关于开展生物医学信息学文献综述的指南,以挑选出2023年发表的KRM领域最佳论文。
我们的检索在PubMed上共得到1666篇出版物。从中,我们确定了15篇论文作为最佳论文的潜在候选者,其中3篇最终被选为KRM部分的最佳论文。候选最佳论文涵盖三个主要主题:知识图谱、知识互操作性和本体论。值得注意的是,入选的三篇最佳论文中有两篇分别探讨了知识图谱嵌入在预测重症监护病房再入院率和测量疾病距离方面的潜力。
2023年KRM部分最佳论文的评选过程展示了广泛的主题,知识图谱嵌入成为支持生物医学机器学习应用的一个有前景的领域。